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The Minuteful - kidney test is an in-vitro diagnostic, home-use urine analysis test system for the semi-quantitative measurement of albumin and creatinine in urine, as well as the presentation of their ratio, the albumin-creatinine ratio (ACR). The system consists of a smartphone application, proprietary Color-Board and an ACR Reagent Strip. The system is available for prescription-use only and is intended for people at risk of kidney disease. Results are used in conjunction with clinical evaluation as an aid in the assessment of kidney health.

The Minuteful - kidney test is comprised of a kit and a smartphone application. It is intended for the semi-quantitative measurement of albumin and creatinine in urine, as well as the presentation of their ratio, the albumin-creatinine ratio (ACR). The Minuteful - kidney test is intended for prescription-use only, as a home-use device to aid in the assessment of kidney health. The results can be used together with clinical evaluation to guide patient care. The device's kit includes a urine receptacle, an ACR Reagent Strip, an absorbing (i.e. "blotting") pad, a proprietary Color-Board and a user manual. The device also consists of an easy-to-use smartphone application, image recognition algorithms, and a physician compendium. The software component of the Minuteful - kidney test consists of both an application (app) and a backend server. Both components encompass different computer vision and machine learning algorithmic components, performing the image analysis activities. The app instructs the user how to accurately administer the test. The Image Validation Transfer System (IVTS) component of the Minuteful - kidney test enables its usage across a wide range of smartphone types and operating systems, essentially making the test platform agnostic.

The provided text describes the Minuteful-kidney test (K222921) and its substantial equivalence to a predicate device (K210069). However, it specifically states that "The rest of the analytical performance studies are still relevant for the modified version of the Minuteful - kidney test, and their summary is available in the predicate device documentation (K210069)." This means the detailed acceptance criteria and the comprehensive study demonstrating the device meets those criteria are not present in this document but are referenced as being in the predicate device's documentation.

Therefore, I can report on the studies performed for K222921 to assert its substantial equivalence, but I cannot provide a table of acceptance criteria and reported device performance from this document for the overall device functionality as those details are in K210069. Nor can I provide information regarding sample sizes for test sets, expert qualifications, adjudication methods, MRMC studies, standalone performance, or ground truth details for K222921's overall performance since those are tied to the K210069 submission.

The studies described in K222921 (the current device) are focused on demonstrating that changes made to the device in K222921 do not negatively impact performance, thus maintaining substantial equivalence to its predicate.

Here's an analysis based solely on the provided text for K222921, noting the limitations:

Acceptance Criteria and Device Performance (Limited to K222921 changes):

Since the comprehensive performance data is referenced in K210069, the "acceptance criteria" discussed here are implicitly related to demonstrating that the modifications in K222921 (e.g., multilingual support, software enhancements) do not degrade the performance previously established for K210069. The studies conducted for K222921 focused on the robustness of the Image Validation Transfer System (IVTS) and the analytical limits of detection.

Study Details (for K222921 specific enhancements):

1. Sample size used for the test set and the data provenance:

   • Limit of Detection (LoD): The document does not specify the sample size for the LoD study for K222921. It mentions the study was designed and executed according to CLSI document EP17-A2.
   • Illumination, Physical, Shadow, Blurriness, Misplaced Urine Stick, Dirty Color-Board Studies: The document refers to "Tested smartphones" and "different conditions," but specific numerical sample sizes (e.g., number of images, tests, or smartphones) are not provided. The data provenance is implied to be laboratory-controlled since these are experimental conditions, but no explicit country of origin or retrospective/prospective nature is stated for these new studies. The overall device is intended for home use, so these validations mimic adverse home conditions.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

   • This information is not provided in the K222921 document. These types of analytical studies typically rely on reference methods or scientifically established standards rather than expert consensus. For the clinical performance, the document refers to the predicate device K210069, where such details would likely be found if applicable.

3. Adjudication method (e.g. 2+1, 3+1, none) for the test set:

   • Not applicable/Not provided for these specific analytical studies. The assessment of whether performance was "not impacted" would likely come from statistical analysis against pre-defined thresholds.

4. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:

   • No MRMC or comparative effectiveness study involving human readers with and without AI assistance is mentioned in the K222921 submission. This device is an in-vitro diagnostic home-use test system where the smartphone app performs the measurement, rather than assisting a human in interpreting diagnostic images. Thus, the concept of "human readers improve with AI" in a traditional MRMC sense does not directly apply to this device's function.

5. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:

   • The core of the described studies (LoD, Illumination, Physical, Shadow, Blurriness, Misplaced Urine Stick, Dirty Color-Board) are indeed standalone performance tests of the device's algorithmic capability to accurately read the test strip under various challenging conditions encountered in a home setting. The device is described as having "image recognition algorithms" and performing "image analysis activities."

6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

   • For the analytical studies described (LoD, Illumination, etc.), the ground truth would be based on controlled experimental conditions and potentially quantitative reference measurements (e.g., known concentrations for LoD, controlled lighting conditions). The document does not specify the exact methods for establishing this ground truth but implies scientific rigor (e.g., "in accordance with guidance provided by the Clinical and Laboratory Standards Institute (CLSI) document EP17-A2"). For the clinical performance aspects, the document refers to K210069.

7. The sample size for the training set:

   • Not provided in the K222921 document. Training set details would typically be part of the initial K210069 submission for the machine learning algorithms.

8. How the ground truth for the training set was established:

   • Not provided in the K222921 document. This information would be found in the K210069 submission, likely involving laboratory-controlled tests with known analyte concentrations and reference methods for accurate measurement.

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The Minuteful - kidney test is an in-vitro diagnostic, home-use urine analysis test system for the semi-quantitative measurement of albumin and creatinine in urine, as well as the presentation of their ratio, the albumin-creatinine ratio (ACR). The system consists of a smartphone application, proprietary Color-Board and an ACR Reagent Strip. The system is available for prescription-use only and is intended for people at risk of kidney disease. Results are intended to be used in conjunction with clinical evaluation as an aid in the assessment of kidney health.

The Minuteful - kidney test is comprised of a kit and a smartphone application. It is intended for the semi-quantitative measurement of albumin and creatinine in urine, as well as the presentation of their ratio, the albumin-creatinine ratio (ACR). The Minuteful - kidney test is intended for prescription-use only, as a home-use device to aid in the assessment of kidney health. The results can be used together with clinical evaluation to guide patient care. The device is provided as a kit that comprises a urine receptacle, an ACR Reagent Strip, an absorbing (i.e. "blotting") pad, a proprietary Color-Board and a user manual. The device also consists of an easy-to-use smartphone application, image recognition algorithms, and a physician compendium. The software component of the Minuteful - kidney test consists of both an application (app) and a backend server. Both components encompass different computer vision and machine learning algorithmic components, performing the image analysis activities. The app instructs the user how to accurately administer the test. The Image Validation Transfer System (IVTS) component of the Minuteful - kidney test enables its usage across a wide range of smartphone types and operating systems, essentially making the test platform agnostic.

Here's a breakdown of the acceptance criteria and study information for the Healthy.io Minuteful - kidney test (K210069), based on the provided document:

Acceptance Criteria and Device Performance for Minuteful - kidney test (K210069)

1. Table of Acceptance Criteria and Reported Device Performance

Note: The document implies acceptance criteria by reporting performance results against the predicate device that demonstrate substantial equivalence.

2. Sample Size Used for the Test Set and Data Provenance

• Sample Size: More than 450 subjects were recruited for the clinical trials.
• Data Provenance: The document does not explicitly state the country of origin. The study was a prospective clinical trial, as subjects were "recruited" and tasks were "completed" within the context of the study.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Their Qualifications

The ground truth was established by comparing the Minuteful - kidney test results to those obtained from a professional user performing the test on the URISCAN Optima Urine Analyzer (predicate device).

• Number of Experts: Not explicitly stated as a count of individual professionals, but referred to as "a professional user." It's implied that this
  professional operated the predicate device.
• Qualifications: "Professional user" suggests trained laboratory or healthcare personnel familiar with operating the URISCAN Optima Urine Analyzer and interpreting its results. Specific credentials (e.g., medical technologist, clinical laboratory scientist, years of experience) are not provided.

4. Adjudication Method for the Test Set

The adjudication method involved a 2-part comparison:

1. A lay user (subject in the clinical trial) performed the test using the Minuteful - kidney test app.
2. A professional user (operating the predicate device, URISCAN Optima Urine Analyzer) then performed the test on the same urine sample.

The professional user was blinded to the results of the lay user until after they had completed their test. This can be considered a form of adjudication where the predicate device's result, as read by a professional, serves as the comparison benchmark. There was no explicit multi-expert consensus or 2+1/3+1 method described for establishing a single "ground truth" independent of the comparison devices; rather, the predicate device's output was the reference.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No, an MRMC comparative effectiveness study was not explicitly done in the sense of comparing multiple human readers with and without AI assistance on the same cases. The study compared a lay user with the AI-powered device to a professional user with a predicate device. It was a method comparison study to show substantial equivalence, not a study evaluating human reader improvement with AI assistance.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

The clinical performance study involved a lay user interacting with the smartphone application and performing the test steps guided by the app. While the app uses "image recognition algorithms" and "machine learning algorithmic components," it is not a purely standalone algorithm-only performance assessment in the sense of a laboratory-based algorithm evaluation without human interaction for image capture and strip preparation. However, the analytical performance testing (Precision, Interference, Limit of Detection, Linearity, Stability) would represent the closest to "standalone" algorithm performance testing, as these evaluate the device's technical capabilities in a controlled environment. The linearity study, showing 100% exact match for every level of albumin, creatinine, and ACR, is a strong indicator of the core algorithm's accuracy at different concentrations.

7. The Type of Ground Truth Used

The ground truth was established by comparison to a legally marketed predicate device (URISCAN Optima Urine Analyzer) operated by a professional user. This is a form of reference standard comparison where the predicate device's output serves as the truth.

8. The Sample Size for the Training Set

The document does not provide information regarding the sample size for the training set used for the device's algorithms.

9. How the Ground Truth for the Training Set Was Established

The document does not provide information on how the ground truth was established for the training set of the device's algorithms. It only describes the ground truth for the clinical performance (test set) comparison.

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The ACR | LAB Urine Analysis Test System is comprised of a smartphone application, a proprietary Color-Board, and ACR Reagent Strips. It is intended for the semi-quantitative detection of albumin and creatinine in urine, as well as the presentation of their ratio. The ACR | LAB Urine Analysis Test System is intended for in-vitro diagnostic use by a healthcare professional in a point of care setting. These results may be used in conjunction with clinical evaluation as an aid in the diagnosis for kidney function.

The ACR | LAB Urine Analysis Test System is comprised of a smartphone application, a proprietary Color-Board and ACR Reagent Strips. It is intended for the semi-quantitative detection of albumin and creatinine in urine, as well as the presentation of their ratio. The device is provided as a kit that is comprised of a canister of 100 FDA-cleared urine test strips (ACON Laboratories Inc. Mission Urinalysis Reagent Strips (Microalbumin/Creatinine) K150330), 10 Color-Boards, and a User Manual. The ACR | LAB Urine Analysis Test System also consists of a smartphone application for use on iPhone 7 device (iOS 12), and an image recognition algorithm running on the Backend. The software component of the ACR | LAB consists of both an application (App) and a Backend server (Backend). The App instructs the professional user how to accurately perform the test. The App conducts a series of boundary condition analyses, and if the scan is approved, sends the information to the Backend for complete analysis and results classification. Once analyzed, the results are securely transmitted to a patient Electronic Medical Record for review by a healthcare professional. The patients do not have access to the results at any point during the testing process.

Here's a breakdown of the acceptance criteria and the study that proves the device meets them, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The core acceptance criteria are based on the agreement between the ACR | LAB Urine Analysis Test System and the predicate device (ACON Laboratories' Mission U120 Ultra Urine Analyzer). The study aimed for high percentages of exact match and ±1 color block match.

| Metric (Agreement with Predicate Device) | Acceptance Criteria (Implicit from "high levels of accuracy") | Reported Device Performance (ACR | LAB) |
| :--------------------------------------- | :----------------------------------------------------------- | :-------------------------------------- |
| Albumin | High Exact Match % | 89% Exact Match |
| Albumin | High ±1 Color Block Match % | 100% ±1 Color Block Match |
| Creatinine | High Exact Match % | 84% Exact Match |
| Creatinine | High ±1 Color Block Match % | 100% ±1 Color Block Match |
| Albumin-Creatinine Ratio | High Exact Match % | 93% Exact Match |
| Albumin-Creatinine Ratio | High ±1 Color Block Match % | 100% ±1 Color Block Match |

Note: The document explicitly states that the primary acceptance criteria for the method comparison study were the percent of exact match and ±1 color block match. While specific numerical targets for "high levels of accuracy" are not given as explicit "acceptance criteria," the reported performance exceeding predicate device agreement in these metrics is implicit evidence of meeting those criteria.

2. Sample Size Used for the Test Set and Data Provenance

• Sample Size:
  • Native Urine Samples: 375 subjects
  • Contrived Samples: 60 samples
  • Total Samples for Clinical Performance: 435 samples (375 native + 60 contrived)
• Data Provenance: The study evaluated native urine samples from 375 subjects as well as 60 contrived samples at three U.S. clinical sites. This indicates the data is prospective (newly collected for the study) and from the United States.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Their Qualifications

The document refers to the predicate device (ACON Laboratories' Mission U120 Ultra Urine Analyzer) as the "ground truth" or reference for comparison.

• Number of "Experts" (for ground truth): The ground truth was established by readings from the predicate device (ACON Laboratories' Mission U120 Ultra Urine Analyzer). Two separate lab technicians measured each urine sample, one using the iPhone 7 device (ACR | LAB) and the second using the predicate device (U120 Ultra).
• Qualifications of "Experts": The document states "Two separate lab technicians were responsible for measuring each urine sample." Their specific qualifications (e.g., years of experience, certifications) are not explicitly mentioned, but they are identified as "lab technicians."

4. Adjudication Method for the Test Set

The adjudication method appears to be none in the traditional sense of multiple human experts reviewing and deciding. Instead, the study directly compared the results of the ACR | LAB device against the results obtained from the predicate device (ACON Laboratories' Mission U120 Ultra Urine Analyzer). Each sample was tested once by the ACR | LAB and once by the predicate device, and the agreement between these two measurements was assessed.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size of Human Improvement

• Was an MRMC study done? No, a traditional MRMC comparative effectiveness study was not done. This study is focused on the performance of a clinical diagnostic device, where consistency with a reference device is key, rather than an AI-assisted interpretation by multiple human readers.
• Effect size of human readers improve with AI vs without AI assistance: This information is not applicable/not provided, as the study design was a direct comparison of the new device to a predicate device, not an assessment of human reader performance with and without AI assistance. The ACR | LAB system itself includes the smartphone app and image recognition algorithm as central components of its operation, so human interaction is inherent, but not a separate "with vs. without AI assistance" arm for human readers.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done

The device description indicates that the "ACR | LAB Urine Analysis Test System is comprised of a smartphone application, a proprietary Color-Board, and ACR Reagent Strips." It also mentions that "The App instructs the professional user how to accurately perform the test. The App conducts a series of boundary condition analyses, and if the scan is approved, sends the information to the Backend for complete analysis and results classification."

This suggests that the device does not operate purely standalone (algorithm-only without human-in-the-loop). A healthcare professional is involved in:
* Performing the physical test (dipping the strip).
* Operating the smartphone application.
* Placing the strip on the Color-Board for scanning.

The algorithm on the Backend performs the complete analysis and classification, but this is initiated and guided by the human user through the app. Therefore, it's a human-in-the-loop system, and no standalone algorithm-only performance is documented separately.

7. The Type of Ground Truth Used

The ground truth for the clinical performance study was established by comparison to a legally marketed predicate device (ACON Laboratories' Mission U120 Ultra Urine Analyzer). The aim was to demonstrate substantial equivalence, meaning the new device's results should align closely with those of the established predicate.

8. The Sample Size for the Training Set

The document does not specify the sample size used for the training set for the image recognition algorithm. It focuses on the validation studies.

9. How the Ground Truth for the Training Set Was Established

The document does not explicitly describe how the ground truth for the training set was established. It broadly mentions the software validation and hazard analysis but doesn't detail the data labeling process for the algorithm's training. It is common for such systems to be trained on a large dataset of images with corresponding known (e.g., laboratory-confirmed) values for albumin and creatinine, but this specific information is not provided here.

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The DIP | U.S. Urine Analysis Test System consists of a smartphone application, a proprietary Color-Board, and Urinalysis Reagent Strips. It is intended for the semi-quantitative detection of the following analytes in urine: Glucose. Specific Gravity, Blood, pH and Protein, as well as the qualitative detection of Nitrite,

The DIP | U.S. Urine Analysis Test System is intended for prescription home-use only, with results provided directly to the physician. The results can be used to guide patient management and care, and aid in the diagnosis and monitoring of metabolic or systemic diseases that affect kidney function and endocrine disorders. Physician interpretation of the results should be made in conjunction with the patient's other clinical information to determine if further confirmatory tests or consultations are necessary. Patients do not have access to the results at any point in the process.

The DIP | U.S. Urine Analysis Test System consists of a smartphone application, a proprietary Color-Board, and Urinalysis Reagent Strips. It is intended for the semi-quantitative detection of the following analytes in urine: Glucose, Specific Gravity, Blood, pH and Protein, as well as the qualitative detection of Nitrite.

The DIP | U.S. Urine Analysis Test System is intended for prescription home-use only, with results provided directly to the physician. The results can be used to guide patient management and care, and aid in the diagnosis and monitoring of metabolic or systemic diseases that affect kidney function and endocrine disorders. Physician interpretation of the results should be made in conjunction with the patient's other clinical information to determine if further confirmatory tests or consultations are necessary. Patients do not have access to the results at any point in the process.

The device is provided as a kit that comprises a urine receptacle, an FDA-cleared urine test strip (ACON Mission Urinalysis Reagent Strips, 510K number K061559), a Color-Board, and a User Manual. The DIP | U.S. Urine Analysis Test System also consists of a smartphone application for use with a LG Nexus 5 device (running operating system Lollipop 5.0), and an image recognition algorithm running on the back-end.

The software component of the DIP | U.S. Urine Analysis Test System consists of both an application and a back-end server. The App instructs the patient how to accurately administer the test and conducts a number of algorithm processes. Once analyzed, the DIP | U.S. Urine Analysis Test System's software securely transmits the clinical results directly to the patient's Electronic Medical Records for review by the physician. As stated above, the patients do not have access to the results at any point during the testing process.

The provided text describes the acceptance criteria and study proving the device meets those criteria for the Healthy.io DIP | U.S. Urine Analysis Test System.

Here's a breakdown of the requested information:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are primarily defined by the "percent exact match" and "±1 color block match" compared to the predicate device (ACON Mission U500 Urinalysis System). The exact numerical acceptance thresholds are not explicitly stated as strict percentages for all analytes, but the narrative implies "high-levels of accuracy" and specific target ranges are mentioned for certain analytes.

Additional Performance Metrics (from Analytical Performance Testing):

• Repeatability: 99.3% exact match
• Reproducibility: 98.5% exact match
• Linearity: At least 89.4% exact match and 100% ±1 color block accuracy.
• Illumination Study: 99.5% exact match
• Boundary Study: 99.5% exact match

2. Sample Sizes Used for the Test Set and Data Provenance

Two method comparison studies were conducted for the test set:

• Study 1:

  • Sample Size: 429 subjects, 500 total samples (including spiked samples). Only 284 results from LG Nexus 5 smartphones were used for performance data.
  • Data Provenance: Two U.S. clinical sites. The studies involved lay-users in a simulated home-use environment. This indicates prospective data collection for the purpose of this validation.

• Study 2:

  • Sample Size: 250 subjects, 289 total samples (including spiked samples).
  • Data Provenance: One U.S.-based clinic. Similar to Study 1, this appears to be prospective data collection in a simulated home-use setting.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Their Qualifications

The ground truth for the comparison studies was established by "a laboratory professional using the predicate (ACON Mission U500 Urinalysis System)" measuring aliquots of the same samples. The specific number of laboratory professionals or their detailed qualifications (e.g., years of experience, specific certifications) are not explicitly stated in the provided text.

4. Adjudication Method for the Test Set

The text describes comparing the DIP system's results to those from a laboratory professional using the predicate device. It does not mention any formal adjudication method (e.g., 2+1, 3+1 consensus) for discrepancies between the device and the predicate. The predicate device's readings appear to be treated as the reference standard (ground truth).

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size of How Much Human Readers Improve with AI vs. Without AI Assistance

This was not a MRMC comparative effectiveness study in the typical sense of evaluating human reader improvement with AI assistance. The study evaluates the performance of the device itself as used by a lay-user, compared to a predicate device operated by a laboratory professional. There is no mention of human readers interpreting images with and without AI assistance to measure improvement.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

The performance data presented, particularly the "Method Comparison Study," represents the device's performance with a human-in-the-loop (lay-user) interacting with the smartphone application and Color-Board. The device itself (including its image recognition algorithm on the back-end) performs the analysis of the test strip after the user interacts with it. The usability results (e.g., 99% success rate for lay users completing the test) address the human-in-the-loop aspect.

However, the "Analytical Performance Testing" (Precision, Interference, Limit of Detection, Linearity, Illumination, Boundary Studies) implicitly evaluates the algorithm's performance under controlled conditions with pre-determined reagent values or spiked samples, which can be seen as a form of standalone evaluation of the core analytical capability. For example, the Illumination Study and Boundary Study evaluate the device's (and thus the algorithm's) ability to measure accurately under varying external conditions. In these studies, the device measured against "predetermined reagent values," which serves as the ground truth for evaluating the algorithm's accuracy under those specific conditions.

7. The Type of Ground Truth Used

The primary ground truth used for the method comparison studies (clinical validation) was the readings obtained from the predicate device (ACON Mission U500 Urinalysis System) by a laboratory professional.

For the analytical performance studies (Precision, Interference, Limit of Detection, Linearity, Illumination, Boundary), the ground truth was based on validated spiked urine solutions at known concentrations or predetermined reagent values.

8. The Sample Size for the Training Set

The provided text does not explicitly state the sample size used for the training set for the image recognition algorithm. It focuses on the validation studies.

9. How the Ground Truth for the Training Set Was Established

The text does not describe how the ground truth for the training set was established. It only mentions that the device includes an "image recognition algorithm running on the back-end." It is standard practice for such algorithms to be trained on large datasets with established ground truth, but the details of this process are not provided in this specific document.

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